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Giant cell arteritis (GCA) is an inflammatory disease causing new, unaccustomed headache in the elderly and which can lead to blindness in 20-30% of untreated cases. The study group have previously shown that ultrasound is a viable non-invasive alternative to temporal artery biopsy in diagnosing GCA. However, there is significant variation in ultrasound assessment (measuring a dark "halo" around the abnormal blood vessels) between sonographers in different centres, requiring a labour intensive and time consuming training programme. The study group propose to standardise the training programme, and use ultrasound and clinical evaluation to define changes occurring over time and with treatment in patients with a diagnosis of GCA made based on ultrasound changes alone. The study group will explore the use of algorithms to automate or semi-automate image interpretation.
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Objectives and Project Plan:
The purpose of the project is to develop the technology to reliably acquire and analyse ultrasound images through the use of a training programme which are comparable to those from scanning by an expert sonographer in the diagnosis (i.e. as a diagnostic tool) and monitoring of patients with GCA following treatment (i.e. as a response indicator), and patient stratification according to initial or early scan changes to determine the most appropriate treatment (i.e. as a prognostic tool).
The end point will be the production of an effective training programme which can be used to obtain reproducible accurate ultrasound images of the temporal artery which can be automatically analysed and used in real time in the management of patients with suspected or confirmed giant cell arteritis.
The project is in 3 phases. In phase 1 (0-12 months) the study group will create a bank of images for training from healthy volunteers and patients with GCA; in phase 2 (13-18 months) the study group will test the programme on sonographers assessing patients with GCA; in phase 3 (19-42 months) the study group will acquire serial images, clinical data, serum and plasma from cohorts of patients with newly diagnosed and flaring GCA so that they can analyse and develop new software algorithms. The study group can use images already acquired from a previous diagnostic study in GCA, and test the algorithms on the new cohorts..
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250 participants in 4 patient groups
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Raashid A Luqmani, DM FRCP; Jana Vaskova
Data sourced from clinicaltrials.gov
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